Overview

Dataset statistics

Number of variables28
Number of observations44401
Missing cells97620
Missing cells (%)7.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.0 MiB
Average record size in memory212.0 B

Variable types

Numeric24
DateTime1
Categorical3

Warnings

mintemp is highly correlated with maxtemp and 3 other fieldsHigh correlation
maxtemp is highly correlated with mintemp and 4 other fieldsHigh correlation
rainfall is highly correlated with raintodayHigh correlation
evaporation is highly correlated with maxtemp and 3 other fieldsHigh correlation
sunshine is highly correlated with humidity3pm and 3 other fieldsHigh correlation
humidity9am is highly correlated with evaporation and 2 other fieldsHigh correlation
humidity3pm is highly correlated with sunshine and 5 other fieldsHigh correlation
pressure9am is highly correlated with pressure3pm and 1 other fieldsHigh correlation
pressure3pm is highly correlated with pressure9amHigh correlation
cloud9am is highly correlated with sunshine and 2 other fieldsHigh correlation
cloud3pm is highly correlated with sunshine and 3 other fieldsHigh correlation
temp9am is highly correlated with mintemp and 4 other fieldsHigh correlation
temp3pm is highly correlated with mintemp and 5 other fieldsHigh correlation
raintoday is highly correlated with rainfallHigh correlation
temp is highly correlated with mintemp and 3 other fieldsHigh correlation
humidity is highly correlated with sunshine and 3 other fieldsHigh correlation
wind_gustdir is highly correlated with wind_dir3pmHigh correlation
wind_gustspeed is highly correlated with pressure9am and 2 other fieldsHigh correlation
wind_dir3pm is highly correlated with wind_gustdirHigh correlation
wind_speed9am is highly correlated with wind_gustspeed and 1 other fieldsHigh correlation
wind_speed3pm is highly correlated with wind_gustspeed and 1 other fieldsHigh correlation
mintemp is highly correlated with maxtemp and 3 other fieldsHigh correlation
maxtemp is highly correlated with mintemp and 4 other fieldsHigh correlation
rainfall is highly correlated with raintodayHigh correlation
evaporation is highly correlated with maxtemp and 4 other fieldsHigh correlation
sunshine is highly correlated with humidity3pm and 4 other fieldsHigh correlation
humidity9am is highly correlated with evaporation and 2 other fieldsHigh correlation
humidity3pm is highly correlated with sunshine and 5 other fieldsHigh correlation
pressure9am is highly correlated with pressure3pmHigh correlation
pressure3pm is highly correlated with pressure9amHigh correlation
cloud9am is highly correlated with sunshine and 3 other fieldsHigh correlation
cloud3pm is highly correlated with sunshine and 3 other fieldsHigh correlation
temp9am is highly correlated with mintemp and 4 other fieldsHigh correlation
temp3pm is highly correlated with mintemp and 6 other fieldsHigh correlation
raintoday is highly correlated with rainfallHigh correlation
temp is highly correlated with mintemp and 4 other fieldsHigh correlation
humidity is highly correlated with sunshine and 4 other fieldsHigh correlation
wind_gustdir is highly correlated with wind_dir3pmHigh correlation
wind_gustspeed is highly correlated with wind_speed9am and 1 other fieldsHigh correlation
wind_dir3pm is highly correlated with wind_gustdirHigh correlation
wind_speed9am is highly correlated with wind_gustspeed and 1 other fieldsHigh correlation
wind_speed3pm is highly correlated with wind_gustspeed and 1 other fieldsHigh correlation
mintemp is highly correlated with temp9amHigh correlation
maxtemp is highly correlated with temp9am and 2 other fieldsHigh correlation
rainfall is highly correlated with raintodayHigh correlation
sunshine is highly correlated with cloud9am and 1 other fieldsHigh correlation
humidity3pm is highly correlated with humidityHigh correlation
pressure9am is highly correlated with pressure3pmHigh correlation
pressure3pm is highly correlated with pressure9amHigh correlation
cloud9am is highly correlated with sunshine and 1 other fieldsHigh correlation
cloud3pm is highly correlated with sunshine and 1 other fieldsHigh correlation
temp9am is highly correlated with mintemp and 3 other fieldsHigh correlation
temp3pm is highly correlated with maxtemp and 2 other fieldsHigh correlation
raintoday is highly correlated with rainfallHigh correlation
temp is highly correlated with maxtemp and 2 other fieldsHigh correlation
humidity is highly correlated with humidity3pmHigh correlation
wind_gustspeed is highly correlated with wind_speed9am and 1 other fieldsHigh correlation
wind_speed9am is highly correlated with wind_gustspeedHigh correlation
wind_speed3pm is highly correlated with wind_gustspeedHigh correlation
raintomorrow is highly correlated with humidity3pm and 2 other fieldsHigh correlation
humidity3pm is highly correlated with raintomorrow and 10 other fieldsHigh correlation
wind_dir9am is highly correlated with location and 2 other fieldsHigh correlation
humidity is highly correlated with raintomorrow and 8 other fieldsHigh correlation
df_index is highly correlated with maxtemp and 6 other fieldsHigh correlation
maxtemp is highly correlated with humidity3pm and 8 other fieldsHigh correlation
cloud3pm is highly correlated with humidity3pm and 2 other fieldsHigh correlation
temp9am is highly correlated with df_index and 5 other fieldsHigh correlation
location is highly correlated with humidity3pm and 13 other fieldsHigh correlation
cloud9am is highly correlated with humidity3pm and 3 other fieldsHigh correlation
wind_gustdir is highly correlated with wind_dir9am and 2 other fieldsHigh correlation
wind_speed9am is highly correlated with wind_speed3pm and 1 other fieldsHigh correlation
sunshine is highly correlated with raintomorrow and 8 other fieldsHigh correlation
pressure9am is highly correlated with wind_gustspeed and 1 other fieldsHigh correlation
wind_dir3pm is highly correlated with wind_dir9am and 2 other fieldsHigh correlation
temp is highly correlated with humidity3pm and 6 other fieldsHigh correlation
wind_speed3pm is highly correlated with wind_speed9am and 1 other fieldsHigh correlation
wind_gustspeed is highly correlated with wind_speed9am and 3 other fieldsHigh correlation
raintoday is highly correlated with humidity3pm and 1 other fieldsHigh correlation
evaporation is highly correlated with maxtemp and 3 other fieldsHigh correlation
humidity9am is highly correlated with humidity3pm and 2 other fieldsHigh correlation
mintemp is highly correlated with df_index and 5 other fieldsHigh correlation
pressure3pm is highly correlated with pressure9am and 1 other fieldsHigh correlation
temp3pm is highly correlated with humidity3pm and 9 other fieldsHigh correlation
evaporation has 20430 (46.0%) missing values Missing
sunshine has 23421 (52.7%) missing values Missing
humidity9am has 612 (1.4%) missing values Missing
humidity3pm has 1414 (3.2%) missing values Missing
pressure9am has 4382 (9.9%) missing values Missing
pressure3pm has 4372 (9.8%) missing values Missing
cloud9am has 16858 (38.0%) missing values Missing
cloud3pm has 18215 (41.0%) missing values Missing
temp3pm has 1062 (2.4%) missing values Missing
humidity has 1414 (3.2%) missing values Missing
wind_gustspeed has 2755 (6.2%) missing values Missing
wind_speed3pm has 867 (2.0%) missing values Missing
df_index has unique values Unique
rainfall has 25575 (57.6%) zeros Zeros
sunshine has 885 (2.0%) zeros Zeros
cloud9am has 2315 (5.2%) zeros Zeros
cloud3pm has 1172 (2.6%) zeros Zeros
wind_gustdir has 2431 (5.5%) zeros Zeros
wind_dir9am has 2017 (4.5%) zeros Zeros
wind_dir3pm has 2241 (5.0%) zeros Zeros
wind_speed9am has 4608 (10.4%) zeros Zeros
wind_speed3pm has 762 (1.7%) zeros Zeros

Reproduction

Analysis started2021-06-05 20:32:01.262230
Analysis finished2021-06-05 20:33:17.774573
Duration1 minute and 16.51 seconds
Software versionpandas-profiling v3.0.0
Download configurationconfig.json

Variables

df_index
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct44401
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82043.85187
Minimum150
Maximum164385
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size347.0 KiB
2021-06-05T17:33:17.875327image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum150
5-th percentile8108
Q140571
median82012
Q3123119
95-th percentile156072
Maximum164385
Range164235
Interquartile range (IQR)82548

Descriptive statistics

Standard deviation47486.56306
Coefficient of variation (CV)0.5787949002
Kurtosis-1.199382759
Mean82043.85187
Median Absolute Deviation (MAD)41148
Skewness0.005064827505
Sum3642829067
Variance2254973671
MonotonicityStrictly increasing
2021-06-05T17:33:17.989029image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
675851
 
< 0.1%
887341
 
< 0.1%
1460661
 
< 0.1%
129471
 
< 0.1%
27081
 
< 0.1%
661971
 
< 0.1%
68061
 
< 0.1%
702951
 
< 0.1%
928241
 
< 0.1%
313861
 
< 0.1%
Other values (44391)44391
> 99.9%
ValueCountFrequency (%)
1501
< 0.1%
1511
< 0.1%
1521
< 0.1%
1531
< 0.1%
1541
< 0.1%
1551
< 0.1%
1561
< 0.1%
1571
< 0.1%
1581
< 0.1%
1591
< 0.1%
ValueCountFrequency (%)
1643851
< 0.1%
1643841
< 0.1%
1643831
< 0.1%
1643821
< 0.1%
1643811
< 0.1%
1643801
< 0.1%
1643791
< 0.1%
1643781
< 0.1%
1643771
< 0.1%
1643761
< 0.1%

date
Date

Distinct884
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size347.0 KiB
Minimum2008-05-01 00:00:00
Maximum2017-06-25 00:00:00
2021-06-05T17:33:18.112149image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:18.232829image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

location
Categorical

HIGH CORRELATION

Distinct49
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size347.0 KiB
Sydney
 
1031
Canberra
 
1027
Perth
 
971
Darwin
 
969
Hobart
 
969
Other values (44)
39434 

Length

Max length16
Median length8
Mean length8.694105989
Min length4

Characters and Unicode

Total characters386027
Distinct characters40
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAlbury
2nd rowAlbury
3rd rowAlbury
4th rowAlbury
5th rowAlbury

Common Values

ValueCountFrequency (%)
Sydney1031
 
2.3%
Canberra1027
 
2.3%
Perth971
 
2.2%
Darwin969
 
2.2%
Hobart969
 
2.2%
Brisbane962
 
2.2%
PerthAirport940
 
2.1%
Dartmoor940
 
2.1%
Mildura940
 
2.1%
Ballarat940
 
2.1%
Other values (39)34712
78.2%

Length

2021-06-05T17:33:18.492160image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
sydney1031
 
2.3%
canberra1027
 
2.3%
perth971
 
2.2%
darwin969
 
2.2%
hobart969
 
2.2%
brisbane962
 
2.2%
perthairport940
 
2.1%
sale940
 
2.1%
melbourneairport940
 
2.1%
cobar940
 
2.1%
Other values (39)34712
78.2%

Most occurring characters

ValueCountFrequency (%)
a36006
 
9.3%
r35771
 
9.3%
o33144
 
8.6%
e31603
 
8.2%
n27372
 
7.1%
l23868
 
6.2%
i23200
 
6.0%
t18206
 
4.7%
d11294
 
2.9%
s11162
 
2.9%
Other values (30)134401
34.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter326159
84.5%
Uppercase Letter59868
 
15.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a36006
11.0%
r35771
11.0%
o33144
10.2%
e31603
9.7%
n27372
 
8.4%
l23868
 
7.3%
i23200
 
7.1%
t18206
 
5.6%
d11294
 
3.5%
s11162
 
3.4%
Other values (12)74533
22.9%
Uppercase Letter
ValueCountFrequency (%)
A8266
13.8%
W7245
12.1%
C5665
9.5%
M5395
9.0%
S4742
7.9%
P4632
7.7%
N4300
7.2%
B3754
 
6.3%
G3639
 
6.1%
H2833
 
4.7%
Other values (8)9397
15.7%

Most occurring scripts

ValueCountFrequency (%)
Latin386027
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a36006
 
9.3%
r35771
 
9.3%
o33144
 
8.6%
e31603
 
8.2%
n27372
 
7.1%
l23868
 
6.2%
i23200
 
6.0%
t18206
 
4.7%
d11294
 
2.9%
s11162
 
2.9%
Other values (30)134401
34.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII386027
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a36006
 
9.3%
r35771
 
9.3%
o33144
 
8.6%
e31603
 
8.2%
n27372
 
7.1%
l23868
 
6.2%
i23200
 
6.0%
t18206
 
4.7%
d11294
 
2.9%
s11162
 
2.9%
Other values (30)134401
34.8%

mintemp
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct338
Distinct (%)0.8%
Missing239
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean8.283232191
Minimum-8.5
Maximum26.6
Zeros112
Zeros (%)0.3%
Negative2520
Negative (%)5.7%
Memory size347.0 KiB
2021-06-05T17:33:18.599847image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-8.5
5-th percentile-0.3
Q14.6
median8.1
Q311.6
95-th percentile18
Maximum26.6
Range35.1
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.434408251
Coefficient of variation (CV)0.6560733933
Kurtosis0.138834052
Mean8.283232191
Median Absolute Deviation (MAD)3.5
Skewness0.2777711097
Sum365804.1
Variance29.53279304
MonotonicityNot monotonic
2021-06-05T17:33:18.715514image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8390
 
0.9%
8.2372
 
0.8%
9368
 
0.8%
7.8367
 
0.8%
8.3365
 
0.8%
7.6363
 
0.8%
9.6361
 
0.8%
6.7360
 
0.8%
6.6358
 
0.8%
7.3357
 
0.8%
Other values (328)40501
91.2%
ValueCountFrequency (%)
-8.51
 
< 0.1%
-8.21
 
< 0.1%
-82
 
< 0.1%
-7.82
 
< 0.1%
-7.52
 
< 0.1%
-7.32
 
< 0.1%
-77
< 0.1%
-6.92
 
< 0.1%
-6.81
 
< 0.1%
-6.75
< 0.1%
ValueCountFrequency (%)
26.61
 
< 0.1%
26.11
 
< 0.1%
25.92
 
< 0.1%
25.812
< 0.1%
25.72
 
< 0.1%
25.63
 
< 0.1%
25.58
< 0.1%
25.42
 
< 0.1%
25.34
 
< 0.1%
25.28
< 0.1%

maxtemp
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct396
Distinct (%)0.9%
Missing99
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean18.21104013
Minimum-4.8
Maximum37
Zeros7
Zeros (%)< 0.1%
Negative83
Negative (%)0.2%
Memory size347.0 KiB
2021-06-05T17:33:18.837192image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-4.8
5-th percentile11
Q114.8
median17.7
Q321
95-th percentile28.2
Maximum37
Range41.8
Interquartile range (IQR)6.2

Descriptive statistics

Standard deviation5.31159768
Coefficient of variation (CV)0.2916690997
Kurtosis1.064367283
Mean18.21104013
Median Absolute Deviation (MAD)3.1
Skewness0.4002570371
Sum806785.5
Variance28.21306991
MonotonicityNot monotonic
2021-06-05T17:33:18.947894image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17443
 
1.0%
16.1420
 
0.9%
17.4413
 
0.9%
17.3412
 
0.9%
18.2407
 
0.9%
14.8406
 
0.9%
15.7399
 
0.9%
17.6398
 
0.9%
16.9396
 
0.9%
17.2394
 
0.9%
Other values (386)40214
90.6%
ValueCountFrequency (%)
-4.82
< 0.1%
-3.71
 
< 0.1%
-3.21
 
< 0.1%
-3.11
 
< 0.1%
-32
< 0.1%
-2.91
 
< 0.1%
-2.71
 
< 0.1%
-2.52
< 0.1%
-2.24
< 0.1%
-2.12
< 0.1%
ValueCountFrequency (%)
371
 
< 0.1%
36.62
 
< 0.1%
36.58
< 0.1%
36.41
 
< 0.1%
36.21
 
< 0.1%
36.13
 
< 0.1%
364
< 0.1%
35.93
 
< 0.1%
35.82
 
< 0.1%
35.72
 
< 0.1%

rainfall
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct409
Distinct (%)0.9%
Missing415
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean2.35071841
Minimum0
Maximum219.6
Zeros25575
Zeros (%)57.6%
Negative0
Negative (%)0.0%
Memory size347.0 KiB
2021-06-05T17:33:19.064888image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31.2
95-th percentile12.8
Maximum219.6
Range219.6
Interquartile range (IQR)1.2

Descriptive statistics

Standard deviation7.472094609
Coefficient of variation (CV)3.178642995
Kurtosis113.3921134
Mean2.35071841
Median Absolute Deviation (MAD)0
Skewness8.118900898
Sum103398.7
Variance55.83219785
MonotonicityNot monotonic
2021-06-05T17:33:19.179612image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
025575
57.6%
0.23706
 
8.3%
0.41365
 
3.1%
0.6845
 
1.9%
0.8722
 
1.6%
1616
 
1.4%
1.2543
 
1.2%
1.4471
 
1.1%
1.6423
 
1.0%
1.8407
 
0.9%
Other values (399)9313
 
21.0%
(Missing)415
 
0.9%
ValueCountFrequency (%)
025575
57.6%
0.194
 
0.2%
0.23706
 
8.3%
0.334
 
0.1%
0.41365
 
3.1%
0.511
 
< 0.1%
0.6845
 
1.9%
0.77
 
< 0.1%
0.8722
 
1.6%
0.94
 
< 0.1%
ValueCountFrequency (%)
219.62
< 0.1%
182.61
< 0.1%
164.22
< 0.1%
1582
< 0.1%
147.81
< 0.1%
1292
< 0.1%
127.61
< 0.1%
126.41
< 0.1%
120.82
< 0.1%
115.21
< 0.1%

evaporation
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct139
Distinct (%)0.6%
Missing20430
Missing (%)46.0%
Infinite0
Infinite (%)0.0%
Mean2.895694798
Minimum0
Maximum46.2
Zeros179
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size347.0 KiB
2021-06-05T17:33:19.293439image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.4
Q11.4
median2.4
Q34
95-th percentile7
Maximum46.2
Range46.2
Interquartile range (IQR)2.6

Descriptive statistics

Standard deviation2.235681326
Coefficient of variation (CV)0.7720707749
Kurtosis17.1260076
Mean2.895694798
Median Absolute Deviation (MAD)1.2
Skewness2.472708748
Sum69412.7
Variance4.998270993
MonotonicityNot monotonic
2021-06-05T17:33:19.410160image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.41231
 
2.8%
1.21223
 
2.8%
11218
 
2.7%
1.81214
 
2.7%
21192
 
2.7%
1.61185
 
2.7%
2.21136
 
2.6%
0.81092
 
2.5%
41047
 
2.4%
2.4959
 
2.2%
Other values (129)12474
28.1%
(Missing)20430
46.0%
ValueCountFrequency (%)
0179
 
0.4%
0.112
 
< 0.1%
0.2397
 
0.9%
0.35
 
< 0.1%
0.4613
1.4%
0.512
 
< 0.1%
0.6898
2.0%
0.720
 
< 0.1%
0.81092
2.5%
0.923
 
0.1%
ValueCountFrequency (%)
46.21
 
< 0.1%
28.62
< 0.1%
28.42
< 0.1%
27.82
< 0.1%
26.42
< 0.1%
24.82
< 0.1%
24.21
 
< 0.1%
241
 
< 0.1%
23.41
 
< 0.1%
20.63
< 0.1%

sunshine
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct117
Distinct (%)0.6%
Missing23421
Missing (%)52.7%
Infinite0
Infinite (%)0.0%
Mean6.030910391
Minimum0
Maximum11.8
Zeros885
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size347.0 KiB
2021-06-05T17:33:19.949498image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1
Q13.3
median6.6
Q39
95-th percentile10.5
Maximum11.8
Range11.8
Interquartile range (IQR)5.7

Descriptive statistics

Standard deviation3.32775756
Coefficient of variation (CV)0.5517836188
Kurtosis-1.12350937
Mean6.030910391
Median Absolute Deviation (MAD)2.7
Skewness-0.3547066031
Sum126528.5
Variance11.07397038
MonotonicityNot monotonic
2021-06-05T17:33:20.073315image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0885
 
2.0%
9.2413
 
0.9%
9.1380
 
0.9%
9.4371
 
0.8%
9.8351
 
0.8%
9.5323
 
0.7%
9.7322
 
0.7%
9.3313
 
0.7%
9303
 
0.7%
9.9297
 
0.7%
Other values (107)17022
38.3%
(Missing)23421
52.7%
ValueCountFrequency (%)
0885
2.0%
0.1234
 
0.5%
0.2240
 
0.5%
0.3157
 
0.4%
0.4130
 
0.3%
0.5104
 
0.2%
0.6116
 
0.3%
0.7143
 
0.3%
0.8136
 
0.3%
0.9119
 
0.3%
ValueCountFrequency (%)
11.81
 
< 0.1%
11.51
 
< 0.1%
11.42
 
< 0.1%
11.310
 
< 0.1%
11.248
 
0.1%
11.188
0.2%
11132
0.3%
10.9157
0.4%
10.8137
0.3%
10.7158
0.4%

humidity9am
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct93
Distinct (%)0.2%
Missing612
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean77.19326772
Minimum5
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size347.0 KiB
2021-06-05T17:33:20.194020image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile47
Q166
median79
Q392
95-th percentile99
Maximum100
Range95
Interquartile range (IQR)26

Descriptive statistics

Standard deviation16.85607278
Coefficient of variation (CV)0.2183619541
Kurtosis-0.1877288245
Mean77.19326772
Median Absolute Deviation (MAD)13
Skewness-0.6071529902
Sum3380216
Variance284.1271895
MonotonicityNot monotonic
2021-06-05T17:33:20.312677image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
992239
 
5.0%
1001906
 
4.3%
981215
 
2.7%
971094
 
2.5%
93939
 
2.1%
82926
 
2.1%
87923
 
2.1%
76921
 
2.1%
96920
 
2.1%
84915
 
2.1%
Other values (83)31791
71.6%
ValueCountFrequency (%)
51
 
< 0.1%
61
 
< 0.1%
82
 
< 0.1%
103
< 0.1%
122
 
< 0.1%
133
< 0.1%
143
< 0.1%
155
< 0.1%
166
< 0.1%
175
< 0.1%
ValueCountFrequency (%)
1001906
4.3%
992239
5.0%
981215
2.7%
971094
2.5%
96920
2.1%
95867
 
2.0%
94877
 
2.0%
93939
2.1%
92912
2.1%
91876
 
2.0%

humidity3pm
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct99
Distinct (%)0.2%
Missing1414
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean57.97259637
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size347.0 KiB
2021-06-05T17:33:20.436376image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile28
Q145
median58
Q370
95-th percentile91
Maximum100
Range99
Interquartile range (IQR)25

Descriptive statistics

Standard deviation18.6172564
Coefficient of variation (CV)0.32113891
Kurtosis-0.4367693547
Mean57.97259637
Median Absolute Deviation (MAD)13
Skewness0.09037788147
Sum2492068
Variance346.602236
MonotonicityNot monotonic
2021-06-05T17:33:20.557050image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
57954
 
2.1%
59953
 
2.1%
53936
 
2.1%
58924
 
2.1%
52920
 
2.1%
55908
 
2.0%
50907
 
2.0%
61896
 
2.0%
64887
 
2.0%
63884
 
2.0%
Other values (89)33818
76.2%
(Missing)1414
 
3.2%
ValueCountFrequency (%)
11
 
< 0.1%
32
 
< 0.1%
42
 
< 0.1%
52
 
< 0.1%
63
 
< 0.1%
712
< 0.1%
87
 
< 0.1%
911
< 0.1%
1015
< 0.1%
1124
0.1%
ValueCountFrequency (%)
100214
0.5%
99198
0.4%
98266
0.6%
97200
0.5%
96215
0.5%
95204
0.5%
94260
0.6%
93236
0.5%
92282
0.6%
91257
0.6%

pressure9am
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct502
Distinct (%)1.3%
Missing4382
Missing (%)9.9%
Infinite0
Infinite (%)0.0%
Mean1020.791861
Minimum980.5
Maximum1040.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size347.0 KiB
2021-06-05T17:33:20.676318image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum980.5
5-th percentile1007.3
Q11016.2
median1021.1
Q31026
95-th percentile1032.3
Maximum1040.5
Range60
Interquartile range (IQR)9.8

Descriptive statistics

Standard deviation7.496990449
Coefficient of variation (CV)0.00734428901
Kurtosis0.5823264222
Mean1020.791861
Median Absolute Deviation (MAD)4.9
Skewness-0.4789726317
Sum40851069.5
Variance56.20486579
MonotonicityNot monotonic
2021-06-05T17:33:20.793008image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1019.6263
 
0.6%
1017.9256
 
0.6%
1017.7248
 
0.6%
1021.1246
 
0.6%
1021.7244
 
0.5%
1019.8241
 
0.5%
1018239
 
0.5%
1018.6237
 
0.5%
1023.2236
 
0.5%
1019.9234
 
0.5%
Other values (492)37575
84.6%
(Missing)4382
 
9.9%
ValueCountFrequency (%)
980.51
 
< 0.1%
982.22
< 0.1%
983.71
 
< 0.1%
983.92
< 0.1%
984.42
< 0.1%
986.61
 
< 0.1%
987.22
< 0.1%
987.91
 
< 0.1%
988.13
< 0.1%
988.21
 
< 0.1%
ValueCountFrequency (%)
1040.51
 
< 0.1%
1040.42
< 0.1%
1040.34
< 0.1%
1040.22
< 0.1%
1040.14
< 0.1%
1039.92
< 0.1%
1039.71
 
< 0.1%
1039.51
 
< 0.1%
1039.41
 
< 0.1%
1039.31
 
< 0.1%

pressure3pm
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct498
Distinct (%)1.2%
Missing4372
Missing (%)9.8%
Infinite0
Infinite (%)0.0%
Mean1018.380578
Minimum977.1
Maximum1039.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size347.0 KiB
2021-06-05T17:33:20.915680image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum977.1
5-th percentile1005.7
Q11013.7
median1018.7
Q31023.6
95-th percentile1029.9
Maximum1039.6
Range62.5
Interquartile range (IQR)9.9

Descriptive statistics

Standard deviation7.392417059
Coefficient of variation (CV)0.007258992579
Kurtosis0.4076772364
Mean1018.380578
Median Absolute Deviation (MAD)4.9
Skewness-0.39183573
Sum40764756.16
Variance54.64782997
MonotonicityNot monotonic
2021-06-05T17:33:21.040346image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1020.3258
 
0.6%
1017.4248
 
0.6%
1020.8247
 
0.6%
1018.7238
 
0.5%
1020.4236
 
0.5%
1018.1236
 
0.5%
1018.4235
 
0.5%
1020.7232
 
0.5%
1018.5231
 
0.5%
1019.2229
 
0.5%
Other values (488)37639
84.8%
(Missing)4372
 
9.8%
ValueCountFrequency (%)
977.12
< 0.1%
978.22
< 0.1%
9791
< 0.1%
981.41
< 0.1%
982.21
< 0.1%
986.12
< 0.1%
986.52
< 0.1%
987.32
< 0.1%
987.41
< 0.1%
987.61
< 0.1%
ValueCountFrequency (%)
1039.61
< 0.1%
1038.91
< 0.1%
1038.41
< 0.1%
1037.81
< 0.1%
1037.61
< 0.1%
1037.51
< 0.1%
1037.31
< 0.1%
1037.21
< 0.1%
1037.11
< 0.1%
10372
< 0.1%

cloud9am
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct10
Distinct (%)< 0.1%
Missing16858
Missing (%)38.0%
Infinite0
Infinite (%)0.0%
Mean4.626729114
Minimum0
Maximum9
Zeros2315
Zeros (%)5.2%
Negative0
Negative (%)0.0%
Memory size347.0 KiB
2021-06-05T17:33:21.147088image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median6
Q37
95-th percentile8
Maximum9
Range9
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.907284926
Coefficient of variation (CV)0.6283672233
Kurtosis-1.521099761
Mean4.626729114
Median Absolute Deviation (MAD)2
Skewness-0.306577426
Sum127434
Variance8.452305643
MonotonicityNot monotonic
2021-06-05T17:33:21.222858image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
76207
 
14.0%
85390
 
12.1%
14862
 
11.0%
62417
 
5.4%
02315
 
5.2%
21944
 
4.4%
31633
 
3.7%
51609
 
3.6%
41165
 
2.6%
91
 
< 0.1%
(Missing)16858
38.0%
ValueCountFrequency (%)
02315
 
5.2%
14862
11.0%
21944
 
4.4%
31633
 
3.7%
41165
 
2.6%
51609
 
3.6%
62417
 
5.4%
76207
14.0%
85390
12.1%
91
 
< 0.1%
ValueCountFrequency (%)
91
 
< 0.1%
85390
12.1%
76207
14.0%
62417
 
5.4%
51609
 
3.6%
41165
 
2.6%
31633
 
3.7%
21944
 
4.4%
14862
11.0%
02315
 
5.2%

cloud3pm
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct9
Distinct (%)< 0.1%
Missing18215
Missing (%)41.0%
Infinite0
Infinite (%)0.0%
Mean4.842816772
Minimum0
Maximum8
Zeros1172
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size347.0 KiB
2021-06-05T17:33:21.303642image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median6
Q37
95-th percentile8
Maximum8
Range8
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.688052576
Coefficient of variation (CV)0.5550597312
Kurtosis-1.338292685
Mean4.842816772
Median Absolute Deviation (MAD)2
Skewness-0.4027374633
Sum126814
Variance7.22562665
MonotonicityNot monotonic
2021-06-05T17:33:21.388416image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
76105
 
13.7%
84700
 
10.6%
13982
 
9.0%
62774
 
6.2%
22015
 
4.5%
51992
 
4.5%
31921
 
4.3%
41525
 
3.4%
01172
 
2.6%
(Missing)18215
41.0%
ValueCountFrequency (%)
01172
 
2.6%
13982
9.0%
22015
 
4.5%
31921
 
4.3%
41525
 
3.4%
51992
 
4.5%
62774
6.2%
76105
13.7%
84700
10.6%
ValueCountFrequency (%)
84700
10.6%
76105
13.7%
62774
6.2%
51992
 
4.5%
41525
 
3.4%
31921
 
4.3%
22015
 
4.5%
13982
9.0%
01172
 
2.6%

temp9am
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct349
Distinct (%)0.8%
Missing253
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean12.33274894
Minimum-7.2
Maximum31.1
Zeros25
Zeros (%)0.1%
Negative313
Negative (%)0.7%
Memory size347.0 KiB
2021-06-05T17:33:21.498122image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-7.2
5-th percentile4.2
Q18.9
median11.9
Q315.4
95-th percentile22.5
Maximum31.1
Range38.3
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation5.318847579
Coefficient of variation (CV)0.4312783473
Kurtosis0.3862451478
Mean12.33274894
Median Absolute Deviation (MAD)3.2
Skewness0.3641800356
Sum544466.2
Variance28.29013957
MonotonicityNot monotonic
2021-06-05T17:33:21.617036image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.5434
 
1.0%
11.5421
 
0.9%
11.2412
 
0.9%
12.5401
 
0.9%
12399
 
0.9%
12.4396
 
0.9%
10395
 
0.9%
11394
 
0.9%
10.8393
 
0.9%
13.8392
 
0.9%
Other values (339)40111
90.3%
ValueCountFrequency (%)
-7.22
 
< 0.1%
-72
 
< 0.1%
-6.21
 
< 0.1%
-5.91
 
< 0.1%
-5.63
< 0.1%
-5.51
 
< 0.1%
-5.31
 
< 0.1%
-5.25
< 0.1%
-4.53
< 0.1%
-4.33
< 0.1%
ValueCountFrequency (%)
31.11
 
< 0.1%
305
 
< 0.1%
29.92
 
< 0.1%
29.74
 
< 0.1%
29.51
 
< 0.1%
29.43
 
< 0.1%
29.22
 
< 0.1%
29.19
< 0.1%
2914
< 0.1%
28.92
 
< 0.1%

temp3pm
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct392
Distinct (%)0.9%
Missing1062
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean16.99877939
Minimum-5.4
Maximum36
Zeros9
Zeros (%)< 0.1%
Negative134
Negative (%)0.3%
Memory size347.0 KiB
2021-06-05T17:33:21.744696image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-5.4
5-th percentile9.8
Q113.6
median16.6
Q319.8
95-th percentile26.5
Maximum36
Range41.4
Interquartile range (IQR)6.2

Descriptive statistics

Standard deviation5.211278326
Coefficient of variation (CV)0.3065677956
Kurtosis1.060845168
Mean16.99877939
Median Absolute Deviation (MAD)3.1
Skewness0.3321633636
Sum736710.1
Variance27.15742179
MonotonicityNot monotonic
2021-06-05T17:33:21.864376image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15424
 
1.0%
17.8413
 
0.9%
15.8404
 
0.9%
16.7401
 
0.9%
16.4400
 
0.9%
17.4396
 
0.9%
17394
 
0.9%
15.5391
 
0.9%
16.6391
 
0.9%
14389
 
0.9%
Other values (382)39336
88.6%
(Missing)1062
 
2.4%
ValueCountFrequency (%)
-5.42
< 0.1%
-5.11
 
< 0.1%
-4.22
< 0.1%
-4.11
 
< 0.1%
-3.92
< 0.1%
-3.82
< 0.1%
-3.73
< 0.1%
-3.54
< 0.1%
-3.24
< 0.1%
-3.12
< 0.1%
ValueCountFrequency (%)
363
< 0.1%
35.52
 
< 0.1%
35.21
 
< 0.1%
351
 
< 0.1%
34.91
 
< 0.1%
34.81
 
< 0.1%
34.63
< 0.1%
34.55
< 0.1%
34.45
< 0.1%
34.33
< 0.1%

raintoday
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing415
Missing (%)0.9%
Memory size347.0 KiB
0.0
32979 
1.0
11007 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters131958
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.032979
74.3%
1.011007
 
24.8%
(Missing)415
 
0.9%

Length

2021-06-05T17:33:22.053869image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-05T17:33:22.111735image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
ValueCountFrequency (%)
0.032979
75.0%
1.011007
 
25.0%

Most occurring characters

ValueCountFrequency (%)
076965
58.3%
.43986
33.3%
111007
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number87972
66.7%
Other Punctuation43986
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
076965
87.5%
111007
 
12.5%
Other Punctuation
ValueCountFrequency (%)
.43986
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common131958
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
076965
58.3%
.43986
33.3%
111007
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII131958
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
076965
58.3%
.43986
33.3%
111007
 
8.3%

raintomorrow
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size347.0 KiB
0
33269 
1
11132 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters44401
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
033269
74.9%
111132
 
25.1%

Length

2021-06-05T17:33:22.249846image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-05T17:33:22.305697image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
ValueCountFrequency (%)
033269
74.9%
111132
 
25.1%

Most occurring characters

ValueCountFrequency (%)
033269
74.9%
111132
 
25.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number44401
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
033269
74.9%
111132
 
25.1%

Most occurring scripts

ValueCountFrequency (%)
Common44401
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
033269
74.9%
111132
 
25.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII44401
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
033269
74.9%
111132
 
25.1%

temp
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2305
Distinct (%)5.2%
Missing99
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean22.76070326
Minimum-3.76
Maximum46.4
Zeros0
Zeros (%)0.0%
Negative23
Negative (%)0.1%
Memory size347.0 KiB
2021-06-05T17:33:22.383488image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-3.76
5-th percentile2.904282858
Q119.04
median22.88
Q326.96
95-th percentile35.6
Maximum46.4
Range50.16
Interquartile range (IQR)7.92

Descriptive statistics

Standard deviation7.797817645
Coefficient of variation (CV)0.3426000311
Kurtosis1.267558198
Mean22.76070326
Median Absolute Deviation (MAD)3.84
Skewness-0.4255213361
Sum1008344.676
Variance60.80596002
MonotonicityNot monotonic
2021-06-05T17:33:22.509152image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22.4415
 
0.9%
21.32403
 
0.9%
22.88396
 
0.9%
22.76388
 
0.9%
22.28386
 
0.9%
19.76386
 
0.9%
23.84384
 
0.9%
23.12378
 
0.9%
20.84374
 
0.8%
22.16373
 
0.8%
Other values (2295)40419
91.0%
ValueCountFrequency (%)
-3.762
< 0.1%
-1.841
 
< 0.1%
-1.721
 
< 0.1%
-1.62
< 0.1%
-1.481
 
< 0.1%
-1.241
 
< 0.1%
-12
< 0.1%
-0.644
< 0.1%
-0.522
< 0.1%
-0.41
 
< 0.1%
ValueCountFrequency (%)
46.41
 
< 0.1%
45.922
 
< 0.1%
45.88
< 0.1%
45.681
 
< 0.1%
45.441
 
< 0.1%
45.323
 
< 0.1%
45.22
 
< 0.1%
45.082
 
< 0.1%
44.962
 
< 0.1%
44.842
 
< 0.1%

humidity
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct1170
Distinct (%)2.7%
Missing1414
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean69.51903937
Minimum2.001065311
Maximum122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size347.0 KiB
2021-06-05T17:33:22.626837image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum2.001065311
5-th percentile28.4
Q153.6
median70.4
Q386
95-th percentile111.2
Maximum122
Range119.9989347
Interquartile range (IQR)32.4

Descriptive statistics

Standard deviation24.8582184
Coefficient of variation (CV)0.3575742505
Kurtosis0.1907381643
Mean69.51903937
Median Absolute Deviation (MAD)15.6
Skewness-0.3110449355
Sum2988414.945
Variance617.931022
MonotonicityNot monotonic
2021-06-05T17:33:22.756491image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
70.4929
 
2.1%
72.8923
 
2.1%
65.6906
 
2.0%
71.6897
 
2.0%
62888
 
2.0%
64.4882
 
2.0%
68880
 
2.0%
75.2871
 
2.0%
78.8864
 
1.9%
77.6860
 
1.9%
Other values (1160)34087
76.8%
(Missing)1414
 
3.2%
ValueCountFrequency (%)
2.0010653111
< 0.1%
2.0021534351
< 0.1%
2.0045095281
< 0.1%
2.0045687921
< 0.1%
2.0063807731
< 0.1%
2.0063987341
< 0.1%
2.0086201431
< 0.1%
2.0124398481
< 0.1%
2.0162588941
< 0.1%
2.0171167521
< 0.1%
ValueCountFrequency (%)
122205
0.5%
120.8193
0.4%
119.6259
0.6%
118.4197
0.4%
117.2206
0.5%
116195
0.4%
114.8244
0.5%
113.6231
0.5%
112.4274
0.6%
111.2245
0.6%

precipitation3pm
Real number (ℝ≥0)

Distinct26
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.02119322
Minimum0
Maximum26
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size347.0 KiB
2021-06-05T17:33:22.869210image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q18
median10
Q312
95-th percentile15
Maximum26
Range26
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.171604935
Coefficient of variation (CV)0.3164897499
Kurtosis0.07693543456
Mean10.02119322
Median Absolute Deviation (MAD)2
Skewness0.3104275011
Sum444951
Variance10.05907786
MonotonicityNot monotonic
2021-06-05T17:33:22.966955image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
105600
12.6%
95475
12.3%
114969
11.2%
84917
11.1%
124213
9.5%
74062
9.1%
133271
7.4%
62808
6.3%
142378
5.4%
51642
 
3.7%
Other values (16)5066
11.4%
ValueCountFrequency (%)
03
 
< 0.1%
120
 
< 0.1%
299
 
0.2%
3340
 
0.8%
4828
 
1.9%
51642
 
3.7%
62808
6.3%
74062
9.1%
84917
11.1%
95475
12.3%
ValueCountFrequency (%)
261
 
< 0.1%
242
 
< 0.1%
2312
 
< 0.1%
2217
 
< 0.1%
2144
 
0.1%
2078
 
0.2%
19180
 
0.4%
18307
 
0.7%
17551
1.2%
16987
2.2%

precipitation9am
Real number (ℝ)

Distinct37223
Distinct (%)83.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.01084637
Minimum-17.73934574
Maximum32.2100807
Zeros0
Zeros (%)0.0%
Negative1039
Negative (%)2.3%
Memory size347.0 KiB
2021-06-05T17:33:23.071647image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum-17.73934574
5-th percentile1.753604315
Q16.691665085
median10.01263219
Q313.4110567
95-th percentile18.19847592
Maximum32.2100807
Range49.94942644
Interquartile range (IQR)6.719391614

Descriptive statistics

Standard deviation5.004913819
Coefficient of variation (CV)0.4999491184
Kurtosis0.02368626227
Mean10.01084637
Median Absolute Deviation (MAD)3.357857044
Skewness-0.01732997515
Sum444491.5899
Variance25.04916234
MonotonicityNot monotonic
2021-06-05T17:33:23.195511image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.5996004892
 
< 0.1%
7.1620032092
 
< 0.1%
8.6941591872
 
< 0.1%
13.479452872
 
< 0.1%
9.4479729552
 
< 0.1%
7.4436323912
 
< 0.1%
1.8147214232
 
< 0.1%
5.3501712312
 
< 0.1%
12.550218672
 
< 0.1%
-1.9347582812
 
< 0.1%
Other values (37213)44381
> 99.9%
ValueCountFrequency (%)
-17.739345741
< 0.1%
-10.302856511
< 0.1%
-9.2109559421
< 0.1%
-9.1325548772
< 0.1%
-8.2351120871
< 0.1%
-7.956289451
< 0.1%
-7.394462441
< 0.1%
-7.3604760262
< 0.1%
-7.109216791
< 0.1%
-7.0281910381
< 0.1%
ValueCountFrequency (%)
32.21008071
< 0.1%
30.243844882
< 0.1%
27.821594671
< 0.1%
27.784125261
< 0.1%
27.64859631
< 0.1%
27.601394131
< 0.1%
27.450358962
< 0.1%
27.348009432
< 0.1%
27.326353921
< 0.1%
26.727001891
< 0.1%

wind_gustdir
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.424157114
Minimum0
Maximum16
Zeros2431
Zeros (%)5.5%
Negative0
Negative (%)0.0%
Memory size173.6 KiB
2021-06-05T17:33:23.295778image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median8
Q313
95-th percentile16
Maximum16
Range16
Interquartile range (IQR)9

Descriptive statistics

Standard deviation4.931994391
Coefficient of variation (CV)0.5854585004
Kurtosis-1.24967899
Mean8.424157114
Median Absolute Deviation (MAD)5
Skewness-0.109888415
Sum374041
Variance24.32456867
MonotonicityNot monotonic
2021-06-05T17:33:23.383546image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
33819
 
8.6%
133819
 
8.6%
143191
 
7.2%
73070
 
6.9%
152857
 
6.4%
162785
 
6.3%
122706
 
6.1%
62669
 
6.0%
112463
 
5.5%
02431
 
5.5%
Other values (7)14591
32.9%
ValueCountFrequency (%)
02431
5.5%
11991
4.5%
22038
4.6%
33819
8.6%
41784
4.0%
52073
4.7%
62669
6.0%
73070
6.9%
82358
5.3%
92123
4.8%
ValueCountFrequency (%)
162785
6.3%
152857
6.4%
143191
7.2%
133819
8.6%
122706
6.1%
112463
5.5%
102224
5.0%
92123
4.8%
82358
5.3%
73070
6.9%

wind_gustspeed
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct60
Distinct (%)0.1%
Missing2755
Missing (%)6.2%
Infinite0
Infinite (%)0.0%
Mean36.36421265
Minimum6
Maximum117
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size347.0 KiB
2021-06-05T17:33:23.494250image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile17
Q126
median33
Q344
95-th percentile65
Maximum117
Range111
Interquartile range (IQR)18

Descriptive statistics

Standard deviation14.63166988
Coefficient of variation (CV)0.4023645451
Kurtosis1.15531716
Mean36.36421265
Median Absolute Deviation (MAD)9
Skewness0.9223271178
Sum1514424
Variance214.0857635
MonotonicityNot monotonic
2021-06-05T17:33:23.605974image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
312431
 
5.5%
282382
 
5.4%
352358
 
5.3%
302337
 
5.3%
332112
 
4.8%
392096
 
4.7%
262094
 
4.7%
242066
 
4.7%
371952
 
4.4%
201796
 
4.0%
Other values (50)20022
45.1%
(Missing)2755
 
6.2%
ValueCountFrequency (%)
61
 
< 0.1%
717
 
< 0.1%
995
 
0.2%
11187
 
0.4%
13522
 
1.2%
15789
1.8%
171153
2.6%
191282
2.9%
201796
4.0%
221564
3.5%
ValueCountFrequency (%)
1171
 
< 0.1%
1133
 
< 0.1%
1113
 
< 0.1%
1091
 
< 0.1%
1077
 
< 0.1%
1065
 
< 0.1%
1045
 
< 0.1%
10210
< 0.1%
1008
< 0.1%
9819
< 0.1%

wind_dir9am
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.60449089
Minimum0
Maximum16
Zeros2017
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size173.6 KiB
2021-06-05T17:33:23.703717image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median8
Q313
95-th percentile16
Maximum16
Range16
Interquartile range (IQR)9

Descriptive statistics

Standard deviation5.023112044
Coefficient of variation (CV)0.583777949
Kurtosis-1.277941985
Mean8.60449089
Median Absolute Deviation (MAD)5
Skewness-0.04038350689
Sum382048
Variance25.23165461
MonotonicityNot monotonic
2021-06-05T17:33:23.790457image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
164934
 
11.1%
34154
 
9.4%
73557
 
8.0%
133186
 
7.2%
142924
 
6.6%
62806
 
6.3%
122763
 
6.2%
52386
 
5.4%
152287
 
5.2%
82043
 
4.6%
Other values (7)13361
30.1%
ValueCountFrequency (%)
02017
4.5%
11774
4.0%
21811
4.1%
34154
9.4%
42001
4.5%
52386
5.4%
62806
6.3%
73557
8.0%
82043
4.6%
91998
4.5%
ValueCountFrequency (%)
164934
11.1%
152287
5.2%
142924
6.6%
133186
7.2%
122763
6.2%
111836
 
4.1%
101924
 
4.3%
91998
4.5%
82043
4.6%
73557
8.0%

wind_dir3pm
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.235557758
Minimum0
Maximum16
Zeros2241
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size173.6 KiB
2021-06-05T17:33:23.881821image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median8
Q313
95-th percentile15
Maximum16
Range16
Interquartile range (IQR)9

Descriptive statistics

Standard deviation4.740821624
Coefficient of variation (CV)0.5756527686
Kurtosis-1.185752167
Mean8.235557758
Median Absolute Deviation (MAD)4
Skewness-0.08826323231
Sum365667
Variance22.47538967
MonotonicityNot monotonic
2021-06-05T17:33:23.970608image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
133529
 
7.9%
33506
 
7.9%
143208
 
7.2%
73166
 
7.1%
63039
 
6.8%
152874
 
6.5%
82768
 
6.2%
122668
 
6.0%
112615
 
5.9%
92570
 
5.8%
Other values (7)14458
32.6%
ValueCountFrequency (%)
02241
5.0%
11969
4.4%
22180
4.9%
33506
7.9%
41995
4.5%
52034
4.6%
63039
6.8%
73166
7.1%
82768
6.2%
92570
5.8%
ValueCountFrequency (%)
161655
3.7%
152874
6.5%
143208
7.2%
133529
7.9%
122668
6.0%
112615
5.9%
102384
5.4%
92570
5.8%
82768
6.2%
73166
7.1%

wind_speed9am
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct37
Distinct (%)0.1%
Missing298
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean12.5047049
Minimum0
Maximum74
Zeros4608
Zeros (%)10.4%
Negative0
Negative (%)0.0%
Memory size347.0 KiB
2021-06-05T17:33:24.075330image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median11
Q317
95-th percentile28
Maximum74
Range74
Interquartile range (IQR)11

Descriptive statistics

Standard deviation8.868374187
Coefficient of variation (CV)0.7092029969
Kurtosis1.336508295
Mean12.5047049
Median Absolute Deviation (MAD)6
Skewness0.872939925
Sum551495
Variance78.64806072
MonotonicityNot monotonic
2021-06-05T17:33:24.180077image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
04608
10.4%
94310
9.7%
133943
 
8.9%
113749
 
8.4%
73613
 
8.1%
63049
 
6.9%
153017
 
6.8%
173012
 
6.8%
192330
 
5.2%
42104
 
4.7%
Other values (27)10368
23.4%
ValueCountFrequency (%)
04608
10.4%
21747
 
3.9%
42104
4.7%
63049
6.9%
73613
8.1%
94310
9.7%
113749
8.4%
133943
8.9%
153017
6.8%
173012
6.8%
ValueCountFrequency (%)
742
 
< 0.1%
673
 
< 0.1%
654
 
< 0.1%
631
 
< 0.1%
611
 
< 0.1%
575
 
< 0.1%
5620
< 0.1%
5416
< 0.1%
5213
< 0.1%
5031
0.1%

wind_speed3pm
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct40
Distinct (%)0.1%
Missing867
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean16.5029632
Minimum0
Maximum87
Zeros762
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size347.0 KiB
2021-06-05T17:33:24.294743image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q19
median15
Q322
95-th percentile31
Maximum87
Range87
Interquartile range (IQR)13

Descriptive statistics

Standard deviation8.768048213
Coefficient of variation (CV)0.531301446
Kurtosis1.042727792
Mean16.5029632
Median Absolute Deviation (MAD)6
Skewness0.7491512514
Sum718440
Variance76.87866946
MonotonicityNot monotonic
2021-06-05T17:33:24.401488image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
134309
 
9.7%
93813
 
8.6%
173794
 
8.5%
113599
 
8.1%
153592
 
8.1%
203099
 
7.0%
193015
 
6.8%
72615
 
5.9%
242119
 
4.8%
222117
 
4.8%
Other values (30)11462
25.8%
ValueCountFrequency (%)
0762
 
1.7%
2659
 
1.5%
41171
 
2.6%
61908
4.3%
72615
5.9%
93813
8.6%
113599
8.1%
134309
9.7%
153592
8.1%
173794
8.5%
ValueCountFrequency (%)
871
 
< 0.1%
831
 
< 0.1%
721
 
< 0.1%
691
 
< 0.1%
651
 
< 0.1%
636
< 0.1%
616
< 0.1%
592
 
< 0.1%
578
< 0.1%
5614
< 0.1%

Interactions

2021-06-05T17:32:12.817455image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:12.958106image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:13.079777image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:13.184500image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:13.285204image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:13.392916image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:13.508610image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:13.615351image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:13.723037image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:13.834766image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:13.944444image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:14.045203image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:14.158898image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:14.271605image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:14.376312image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:14.481009image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:14.591741image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:14.702447image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:14.811153image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:14.925836image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:15.034546image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:15.149765image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:15.263439image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:15.374171image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:15.478860image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:15.592584image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:15.705281image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:15.807011image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:15.909731image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:16.008474image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:16.115159image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:16.221897image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:16.434639image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:16.543352image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:16.650119image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:16.746861image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:16.858533image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:16.970265image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:17.074982image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:17.179555image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:17.287274image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:17.398006image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:17.512694image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:17.626396image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:17.737099image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:17.851793image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:17.967483image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:18.081152image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:18.189890image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:18.290618image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:18.393343image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:18.484092image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:18.573861image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:18.672568image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:18.780308image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:18.874030image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:18.969802image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:19.079508image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:19.185225image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:19.280941image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:19.389678image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:19.490381image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:19.582135image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:19.673997image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:19.773708image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:19.871470image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:19.968210image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:20.069915image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:20.167682image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:20.270407image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:20.373127image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:20.472866image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:20.568604image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:20.672332image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:20.897724image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:20.990474image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:21.083205image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:21.184138image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:21.290824image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:21.387566image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:21.485329image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:21.589056image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:21.688760image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:21.780514image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:21.884267image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:21.987960image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:22.085698image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:22.186429image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:22.292165image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:22.398860image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:22.505574image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:22.614312image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:22.715527image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:22.821240image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:22.925964image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:23.029688image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:23.123436image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:23.230149image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:23.326863image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:23.430614image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:23.534310image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:23.631049image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:23.730970image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:23.828679image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:23.927288image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:24.029373image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:24.128112image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:24.227042image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:24.327748image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:24.429476image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:24.528394image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:24.622135image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:24.720871image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:24.816620image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:24.913361image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:25.014083image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:25.112670image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:25.216422image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:25.317124image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:25.416887image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:25.518585image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:25.629312image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:25.733039image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:25.833742image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:25.938490image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:26.036232image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:26.291545image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:26.392277image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:26.493006image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:26.596816image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:26.702506image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:26.798279image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:26.903997image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:27.006692image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:27.111442image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:27.212168image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:27.317860image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:27.421583image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:27.524307image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:27.630667image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:27.730400image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:27.837114image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:27.943829image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:28.053509image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:28.177177image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:28.284415image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:28.391151image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:28.485972image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:28.579331image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:28.672106image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:28.773818image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:28.870339image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:28.971133image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:29.074814image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:29.176519image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:29.270268image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:29.378009image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:29.484695image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:29.583430image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:29.683163image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:29.789901image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:29.892626image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:29.995354image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:30.103041image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:30.210753image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:30.326442image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:30.441136image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:30.554833image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:30.658554image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:30.773277image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:30.880989image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:30.977700image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:31.075466image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:31.171213image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:31.273936image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:31.377630image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:31.482351image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:31.592076image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:31.697572image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:31.796336image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:31.903119image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:32.009864image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:32.108649image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:32.207357image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:32.313114image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:32.416825image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:32.521563image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:32.632232image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:32.736784image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:33.034015image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:33.143720image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:33.251406image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:33.350141image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:33.461230image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:33.569966image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:33.677674image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:33.780147image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:33.880631image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:33.989341image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:34.094165image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:34.202874image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:34.315826image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:34.425503image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:34.526262image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:34.638961image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:34.747669image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:34.859343image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:34.963094image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:35.073769image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:35.182479image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:35.295412image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:35.416089image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:35.530782image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:35.650462image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:35.768355image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:35.885042image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:35.993776image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:36.109442image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:36.222141image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:36.333842image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:36.441563image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:36.544279image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:36.656977image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:36.765714image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:36.874395image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:36.986127image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:37.094860image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:37.196439image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:37.308140image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:37.420870image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:37.536408image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:37.648081image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:37.763800image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:37.873505image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:37.982216image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:38.095912image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:38.207584image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:38.323275image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:38.436997image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:38.550695image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:38.655385image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:38.758136image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:38.854954image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:38.952663image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:39.044441image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:39.149363image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:39.244134image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:39.335760image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:39.433470image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:39.534225image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:39.635929image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:39.727711image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:39.840383image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:39.937677image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:40.036412image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:40.128165image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:40.228895image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:40.325611image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:40.423349image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:40.525077image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:40.619855image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:40.720562image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:40.821375image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:40.922201image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:41.014923image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:41.347064image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:41.456741image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:41.566475image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:41.668758image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:41.771483image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:41.879199image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:41.984617image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:42.090336image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:42.201274image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:42.311978image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:42.425676image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:42.537258image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:42.645973image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:42.755678image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:42.858376image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:42.968110image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:43.076816image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:43.186526image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:43.295235image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:43.400641image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:43.515344image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:43.631026image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:43.743696image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:43.854428image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:43.969116image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:44.080822image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:44.183542image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:44.284276image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:44.392986image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:44.501698image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:44.608961image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:44.715966image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:44.825673image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:44.933412image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:45.031154image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:45.142850image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:45.257549image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:45.360271image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:45.472941image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:45.617554image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:45.742221image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:45.865889image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:45.983575image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:46.093305image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:46.207356image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:46.322049image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:46.438737image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:46.546452image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:46.647152image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:46.747905image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:46.837673image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:46.928423image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:47.029150image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:47.137839image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:47.233935image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:47.330751image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:47.448436image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:47.558203image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:47.660928image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:47.774629image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:47.876359image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:47.969100image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:48.065822image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:48.169545image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:48.270276image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:48.372028image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:48.478303image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:48.577394image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:48.684114image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:48.788834image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:48.891531image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:48.987171image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:49.091417image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:49.199106image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:49.294373image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:49.390112image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:49.484840image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:49.587565image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:49.683343image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:49.784039image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:49.886792image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:49.987495image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:50.082242image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:50.193966image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:50.299684image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:50.404380image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:50.511095image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:50.621798image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:50.729510image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:50.835226image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:50.947927image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:51.054640image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:51.164346image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:51.283029image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:51.711882image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:51.815555image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:51.927258image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:52.036990image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:52.136724image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:52.238424image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:52.341149image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:52.454845image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:52.565549image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:52.671571image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:52.784243image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:52.892982image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:52.992712image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:53.104414image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:53.213123image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:53.310834image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:53.411777image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:53.520480image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:53.629192image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:53.737903image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:53.848579image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:53.956291image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:54.067992image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:54.181689image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:54.296382image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:54.401130image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:54.510354image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:54.619092image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:54.718825image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:54.818530image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:54.919719image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:55.026430image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:55.128131image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:55.230883image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:55.334606image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:55.442318image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:55.541053image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:55.651753image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:55.763431image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:55.863193image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:55.963922image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:56.068642image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:56.174332image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:56.282063image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:56.394541image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:56.499288image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:56.609992image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:56.720699image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:56.830403image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:56.932130image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:57.039846image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:57.150541image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:57.247291image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:57.343035image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:57.439744image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:57.544489image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:57.648068image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:57.754782image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:57.863491image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:57.968252image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:58.064975image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:58.179647image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:58.291347image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:58.397781image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:58.499528image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:58.608243image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:58.715927image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:58.821672image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:58.932348image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:59.037095image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:59.149794image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:59.260200image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:59.369907image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:59.472604image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:59.592284image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:59.741884image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:59.849596image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:32:59.956310image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:00.062027image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:00.177638image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:00.291334image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:00.410017image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:00.525738image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:00.643426image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:00.751109image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:00.869816image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:00.985483image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:01.098300image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:01.209244image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:01.321940image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:01.437633image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:01.551333image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:01.669984image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:01.783731image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:01.905428image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:02.027022image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:02.148673image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:02.262389image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:02.377062image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:02.485771image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:02.582512image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:02.683243image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:02.780006image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:02.881735image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:02.982470image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:03.084197image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:03.190727image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:03.291875image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:03.387641image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:03.495332image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:03.605038image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:03.706790image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:03.808493image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:03.916228image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:04.020951image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:04.467751image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:04.577464image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:04.682822image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:04.793977image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:04.907665image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:05.016984image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:05.118715image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:05.233407image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:05.348136image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:05.452884image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:05.560591image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:05.667310image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:05.781976image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:05.892707image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:06.003406image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:06.118109image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:06.231345image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:06.336064image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:06.455716image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:06.572432image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:06.681136image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:06.788824image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:06.902521image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:07.016217image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:07.131930image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:07.248101image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:07.357830image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:07.472934image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:07.590618image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:07.708308image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:07.819012image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:07.935711image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:08.052399image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:08.161247image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:08.267458image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:08.373206image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:08.486898image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:08.601301image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:08.718986image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:08.837667image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:08.954379image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:09.061093image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:09.178896image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:09.292593image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:09.399279image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:09.509983image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:09.624676image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:09.738372image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:09.852202image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:09.969888image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:10.083923image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:10.202633image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:10.321314image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:10.438995image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:10.549676image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:10.664401image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:10.778065image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:10.882513image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:10.985208image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:11.088965image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:11.205617image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:11.312032image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:11.419771image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:11.531474image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:11.644173image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:11.746325image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:11.861019image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:11.973743image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:12.078463image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:12.185936image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:12.298634image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:12.409338image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:12.522031image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:12.641688image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:12.755385image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:12.872097image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:12.987763image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:13.106445image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:13.215184image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:13.318878image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:13.428610image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:13.525348image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:13.619090image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:13.720829image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:13.832530image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:13.931267image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:14.031996image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:14.137709image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:14.247423image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:14.341165image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:14.449878image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:14.553602image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:14.647350image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:14.743638image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:14.847361image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:14.948123image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:15.049854image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:15.154569image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:15.256293image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:15.365048image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:15.471761image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-06-05T17:33:15.577480image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Correlations

2021-06-05T17:33:24.534130image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-06-05T17:33:24.810391image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-06-05T17:33:25.083655image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-06-05T17:33:25.358920image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2021-06-05T17:33:25.588313image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-06-05T17:33:15.802891image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
A simple visualization of nullity by column.
2021-06-05T17:33:16.667563image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2021-06-05T17:33:17.194127image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2021-06-05T17:33:17.593087image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

df_indexdatelocationmintempmaxtemprainfallevaporationsunshinehumidity9amhumidity3pmpressure9ampressure3pmcloud9amcloud3pmtemp9amtemp3pmraintodayraintomorrowtemphumidityprecipitation3pmprecipitation9amwind_gustdirwind_gustspeedwind_dir9amwind_dir3pmwind_speed9amwind_speed3pm
01502009-05-01Albury1.817.00.0NaNNaN77.044.01026.01023.2NaNNaN7.216.30.0022.40000054.8618.2806791219.016150.07.0
11512009-05-02Albury7.219.20.0NaNNaN81.049.01026.91024.08.04.010.119.10.0025.04000060.81210.3511551222.01137.06.0
21522009-05-03Albury4.618.90.0NaNNaN75.051.01028.71025.9NaNNaN10.618.50.0024.68000063.21211.468518815.03104.07.0
31532009-05-04Albury4.219.10.0NaNNaN86.044.01029.81027.3NaNNaN9.618.80.002.73330454.8188.0196101319.01156.013.0
41542009-05-05Albury5.218.80.0NaNNaN71.047.01031.41028.1NaNNaN10.318.40.0024.56000058.477.733560215.01690.07.0
51552009-05-06Albury4.119.30.0NaNNaN82.049.01028.51024.6NaNNaN10.019.20.0025.16000060.8219.6385151220.01146.07.0
61562009-05-07Albury3.218.40.0NaNNaN86.049.01026.21023.6NaNNaN8.318.20.0024.08000060.855.2138411220.09146.011.0
71572009-05-08Albury4.319.00.0NaNNaN68.036.01028.81025.8NaNNaN11.018.50.0024.80000045.21517.7200851315.016130.09.0
81582009-05-09Albury3.720.50.0NaNNaN78.045.01026.01021.8NaNNaN9.420.20.0026.60000056.0144.2213051317.016150.07.0
91592009-05-10Albury5.419.50.0NaNNaN69.040.01025.11022.3NaNNaN11.719.10.0025.40000050.01416.083703917.01690.07.0

Last rows

df_indexdatelocationmintempmaxtemprainfallevaporationsunshinehumidity9amhumidity3pmpressure9ampressure3pmcloud9amcloud3pmtemp9amtemp3pmraintodayraintomorrowtemphumidityprecipitation3pmprecipitation9amwind_gustdirwind_gustspeedwind_dir9amwind_dir3pmwind_speed9amwind_speed3pm
443911643762017-06-20Uluru3.521.80.0NaNNaN59.027.01024.71021.2NaNNaN9.420.90.0028.1634.4125.848681031.02015.013.0
443921643772017-06-20Uluru3.521.80.0NaNNaN59.027.01024.71021.2NaNNaN9.420.90.0028.1634.4125.848681031.02015.013.0
443931643782017-06-21Uluru2.823.40.0NaNNaN51.024.01024.61020.3NaNNaN10.122.40.0030.0830.8106.653879031.09113.011.0
443941643792017-06-21Uluru2.823.40.0NaNNaN51.024.01024.61020.3NaNNaN10.122.40.0030.0830.8106.653879031.09113.011.0
443951643802017-06-22Uluru3.625.30.0NaNNaN56.021.01023.51019.1NaNNaN10.924.50.0032.3627.2919.715976622.09313.09.0
443961643812017-06-22Uluru3.625.30.0NaNNaN56.021.01023.51019.1NaNNaN10.924.50.0032.3627.2919.715976622.09313.09.0
443971643822017-06-23Uluru5.426.90.0NaNNaN53.024.01021.01016.8NaNNaN12.526.10.0034.2830.8120.985551337.09149.09.0
443981643832017-06-23Uluru5.426.90.0NaNNaN53.024.01021.01016.8NaNNaN12.526.10.0034.2830.8120.985551337.09149.09.0
443991643842017-06-24Uluru7.827.00.0NaNNaN51.024.01019.41016.53.02.015.126.00.0034.4030.8154.381481928.010313.07.0
444001643852017-06-24Uluru7.827.00.0NaNNaN51.024.01019.41016.53.02.015.126.00.0034.4030.8154.381481928.010313.07.0